Mixture models for quantitative HIV RNA data

Research output: Contribution to journalReview articlepeer-review

Abstract

Clinical investigators are increasing their use of quantitative determinations of HIV viral load in their study populations. The distributions of these measures may be highly skewed, left-censored, and with an extra spike below the detection limit of the assay. We recommend use of a mixture model in this situation, with two sets of explanatory covariates. We extend this model to incorporate multiple measures across time, and to employ shared parameters as a way of increasing model efficiency and parsimony. Data from a cohort of HIV-infected men are used to illustrate these features, and simulations are performed to assess the utility of shared parameters.

Original languageEnglish (US)
Pages (from-to)317-325
Number of pages9
JournalStatistical Methods in Medical Research
Volume11
Issue number4
DOIs
StatePublished - Aug 2002

ASJC Scopus subject areas

  • Epidemiology
  • Statistics and Probability
  • Health Information Management

Fingerprint Dive into the research topics of 'Mixture models for quantitative HIV RNA data'. Together they form a unique fingerprint.

Cite this